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10/29/2022
Auxo: Heterogeneity-Mitigating Federated Learning via Scalable Client Clustering
Federated learning (FL) is an emerging machine learning (ML) paradigm th...
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10/28/2022
Coverage-centric Coreset Selection for High Pruning Rates
One-shot coreset selection aims to select a subset of the training data,...
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06/09/2022
Swan: A Neural Engine for Efficient DNN Training on Smartphone SoCs
The need to train DNN models on end-user devices (e.g., smartphones) is ...
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01/17/2022
Efficient DNN Training with Knowledge-Guided Layer Freezing
Training deep neural networks (DNNs) is time-consuming. While most exist...
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07/21/2021
Fed-ensemble: Improving Generalization through Model Ensembling in Federated Learning
In this paper we propose Fed-ensemble: a simple approach that bringsmode...
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05/24/2021
FedScale: Benchmarking Model and System Performance of Federated Learning at Scale
We present FedScale, a diverse set of challenging and realistic benchmar...
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10/12/2020
